Development of a Digital Decision-Making Algorithm to Increase Agricultural Productivity

DOI

10.2991/aebmr.k.200502.214How to use a DOI?

Keywords

digital decision-making algorithm, agricultural productivity, agro-climatic factors, regression equations

Abstract

The paper is devoted to the development of a digital decision-making algorithm in the field of agricultural productivity. The agro-industrial complex is currently one of the most promising areas of application of modern digital technologies. At the same time, the most important branch of agriculture is crop production, in which, at present, the transition to digital technologies is carried out quite poorly. The solution to this problem can be digital technologies, which are designed to solve a number of tasks, the key of which is to increase the productivity of crop production enterprises. It is obvious that the current climate changes can have significant impact on the results of the activities of a number of agricultural enterprises, which requires the development of special corrective measures, as a rule, using agricultural technologies. In this paper, a grain mass is taken as an indicator of productivity. Productivity was assessed by studying the influence of agro-climatic factors on it, including temperature and humidity indicators. In addition, the calculations include the presence or absence of fertilizers, as well as factors related to the technology of cultivation – the seeding rate and sowing dates. The influence of agro-climatic factors on the wheat grain mass was evaluated by regression analysis using the least squares method. The result of this research is the developed regression equations of the influence of agro-climatic factors on the grain mass. Further studies were based on forecasts of agro-climatic factors, which made it possible to predict the grain mass for the next three-year period. The obtained data allow us to make an optimal choice of sowing dates and seeding rates, taking into account the forecast of temperature and humidity. In order to further use the obtained equations, a digital decision-making algorithm was developed, which can become the basis for the development of a decision support system. The obtained digital decision-making algorithm allows you to make forecasts of grain mass for the upcoming period by selecting the optimal sowing dates and seeding rates.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - I N Besaliev
AU  - I P Bolodurina
AU  - S S Akimov
PY  - 2020
DA  - 2020/05/05
TI  - Development of a Digital Decision-Making Algorithm to Increase Agricultural Productivity
BT  - Proceedings of the 2nd International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2020)
PB  - Atlantis Press
SP  - 1287
EP  - 1292
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200502.214
DO  - 10.2991/aebmr.k.200502.214
ID  - Besaliev2020
ER  -